ABSTRACT Adaptation is a fundamental feature of visual processing that enables the nervous system to adjust to features of our surrounding environment. The temporal statistics of natural scenes and saccadic eye movements suggest that in most animals, visual input changes at time scales on the order of hundreds of milliseconds. A proposed function for adaptation is to reduce neurons? responsivity to same or similar visual input over time, thus maximizing stimulus information while reducing redundancy of encoding. Identification of the mechanisms involved in adaptation can reveal how basic biological principles imbue neurons with the ability to perform this kind of computation. Previous studies have largely used stimuli presented for much longer time scales?on the order of tens of seconds?to identify mechanisms underlying adaptation in primary visual cortex (V1). Our lab has identified a form of rapid adaptation in V1 where presentation of a brief, 100 ms static grating is sufficient to suppress responses to subsequent stimuli for seconds. Preliminary data I have collected using in vivo whole-cell recordings in awake mice has shown that in V1 neurons, adaptation is characterized by a reduction in stimulus- evoked excitatory and inhibitory inputs. Here, we seek to test the hypothesis that adaptation to brief stimuli is primarily mediated by reduction in synaptic inputs that cells receive through activity-dependent reduction of feedforward synapses between layer 4 and layer 2/3. Proposed experiments will use in vivo recordings with causal manipulations to address how rapid adaptation could be generated within V1. In Aim 1, I will address potential mechanisms that could contribute to adaptation in addition to changes in synaptic inputs, such as changes in cell-intrinsic properties. In Aim 2, I will further characterize activity-induced changes in synaptic inputs by manipulating the number and orientation of stimuli presented. Finally, in Aim 3 I will specify where these changes could occur within V1 circuitry using layer-specific optogenetic manipulation of feedforward or recurrent pathways. Altogether, the findings of this proposal will improve our understanding of how features of cortical circuits enable the brain to dynamically and efficiently encode stimulus information at naturalistic time scales.